Apply isort and black reformatting

Signed-off-by: JimmyZhang12 <JimmyZhang12@users.noreply.github.com>

nemo/collections/nlp/models/language_modeling/megatron/gpt_full_te_layer_autocast_spec.py

@@ -36,11 +36,11 @@
 try:
     from megatron.core import parallel_state, tensor_parallel
     from megatron.core.fusions.fused_layer_norm import FusedLayerNorm
+    from megatron.core.transformer.graphs import CudaGraphManager
     from megatron.core.transformer.spec_utils import ModuleSpec
     from megatron.core.transformer.transformer_block import TransformerBlockSubmodules, get_num_layers_to_build
     from megatron.core.transformer.transformer_layer import BaseTransformerLayer
     from megatron.core.transformer.utils import make_sharded_tensors_for_checkpoint
-    from megatron.core.transformer.graphs import CudaGraphManager
 
     HAVE_MEGATRON_CORE = True
 
@@ -241,9 +241,7 @@ def __init__(self, config, layer_number=1, hidden_dropout=None):
         super().__init__(**transformer_layer_args)
 
         if not hasattr(self.config, 'external_cuda_graph') and config.enable_cuda_graph and self.training:
-            assert (
-                not config.cpu_offloading and config.recompute_granularity is None
-            ), "Cudagraphs not supported"
+            assert not config.cpu_offloading and config.recompute_granularity is None, "Cudagraphs not supported"
             self.add_module('cudagraph_manager', CudaGraphManager())
 
     # Called by MCore's TransformerBlock.forward
@@ -334,6 +332,7 @@ def __call__(self, *args, **kwargs):
             return self.cudagraph_manager(self, args, kwargs)
         return super().__call__(*args, **kwargs)
 
+
 # Use this spec to use the full Transformer layer from Transformer Engine
 def get_gpt_full_te_layer_autocast_spec(transformer_config) -> ModuleSpec:
     if not HAVE_MEGATRON_CORE or not HAVE_TE: